Discrete element modelling of rock creep behaviour using rate process theory
Bibliographic record
Abstract
Rock creep behaviour is crucial in many rock engineering projects. Different approaches have been proposed to model rock creep behaviour; however, many cannot reproduce tertiary creep (i.e., accelerating strain rates leading to rock failure). In this work, the distinct element method (DEM) is employed, in conjunction with the rate process theory (RPT) of M.R. Kuhn and J.K. Mitchell (published in 1992) to simulate rock creep. The DEM numerical sample is built using a mixture of contact models between particles that combines the Flat Joint Contact Model and the Linear Model. Laboratory uniaxial compression creep tests conducted on intact slate samples are used as a benchmark to validate the methodology. Results demonstrate that, when properly calibrated, DEM models combined with the RPT can reproduce all creep stages observed in slate rock samples in the laboratory, including tertiary creep, without using constitutive models that incorporate an explicit dependence of strain rate on time. The DEM results also suggest that creep is associated with damage in the samples during the laboratory tests, due to new microcracks that appear when the load is applied and maintained constant at each loading stage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".